I. Field of the Invention
This disclosure relates generally to apparatus and methods for camera-based navigation based on image processing. More particularly, the disclosure relates to camera-based pedestrian navigation for indoor and urban environments, where satellite reception is unavailable, restricted, or nonexistent, based on image processing and feature interpretation.
II. Background
Many personal navigation devices (PNDs) include a Global Navigation Satellite System (GNSS), which receives GNSS signals and provides outdoor navigation. When GNSS signals are partially blocked, such as in an urban environment, determined position estimates deteriorates. When GNSS signals are available but inadequate, a PND may supplement a GNSS-based position estimate with one or more terrestrial-based positioning methods.
When GNSS signals are totally blocked, such as when indoors, a PND has no GNSS signals to compute a position estimate. To compensate for weak or blocked GNSS signals, a PND may use multiple terrestrial-based positioning methods to compute a position estimate. Alternatively, a PND may implement position estimation based solely on a terrestrial-based positioning method. One such terrestrial-based positioning method uses cellular-based position location techniques. Unfortunately, cellular-based techniques often result in a position location having a low resolution and an unacceptable high level of uncertainty.
Another such terrestrial-based positioning method is an inertial navigation system (INS), which may use dead reckoning to form a position estimate. Dead reckoning uses inertial sensor measurements to accumulate movement. Inertial sensors, such as MEMS accelerometers and/or MEMS gyrometers, integrate and accumulate movement to determine a step of movement. That is, a position estimate from dead reckoning is based on a determined incremental change in position summed with a previous position estimate.
Each new position estimate also accumulates position error from current inertial measurements with errors from past position estimates. Each inertial sensor measurement may include 3-5% of error and each time this error is summed to form a new position estimate, the error accumulates, therefore an estimated position may quickly depart from an actual position.
Dead reckoning may be improved by localizing transmissions from an access point (AP). For example, a mobile device may determine its position using a location of a known WIFI base station. Such locations must be determined using by a priori mapping, triangulation, signal strength and/or round-trip delay computations. These radio techniques may be difficult to model and may require extensive calibration and measurements across a large number of sampled positions within building (e.g., a measurement may be taken at least once within every square meter to map building) and may still result in low precision or low resolution position estimates. Therefore an improved method for position estimate is desired.